Lifelong Optimization

Abstract

Optimization solvers should learn to improve their performance over time. By learning both during the course of solving an optimization problem as well as across multiple optimization problems, we have demonstrated significant advances in the state of the art in scheduling, packing and related resource constrained combinatorial optimization problems.

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Document Details

Document Type
Technical Report
Publication Date
Apr 13, 2015
Accession Number
ADA614742

Entities

People

  • Pascal Van Hentenryck
  • Peter Stuckey
  • Toby Walsh

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Australia
  • Computational Science
  • Computer Programming
  • Computer Science
  • Computers
  • Demographic Cohorts
  • Department Of Defense
  • Genetic Algorithms
  • Information Operations
  • Learning
  • Mathematical Programming
  • Optimization
  • Prototypes
  • Scheduling (Production)

Fields of Study

  • Computer science

Readers

  • Military History of the United States in the 20th Century.
  • Operations Research